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BitsBound MCP Server

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process_contract

Analyze contracts through an 8-stage pipeline to generate redlines as OOXML Track Changes and optional negotiation emails.

Instructions

Process a contract through the full 8-stage BitsBound pipeline.

⚠️ BEFORE CALLING THIS TOOL: You MUST gather the following information from the user:

REQUIRED - Ask the user:

  1. representingParty: "Are you representing the Customer (buyer) or Vendor (seller)?"

  2. aggressivenessLevel: "On a scale of 1-10, how aggressive should the redlines be? (1=very conciliatory, 5=balanced, 10=very aggressive)"

RECOMMENDED - Ask if not obvious: 3. paperOwnership: "Did the counterparty draft this contract (their paper) or did you draft it (our paper)?" 4. dealValue + dealValueCurrency: "What's the estimated deal value?" 5. industry: "What industry is this contract for?" 6. additionalContext: "Any special context about this deal or relationship I should know?"

FOR EMAIL GENERATION - Ask: 7. emailRecipient: "Should I generate a negotiation email to send to the counterparty?" 8. If yes: recipientName, senderName (your name), any additionalContext for the email tone

After gathering this context, call the tool. The response includes "importantNote" with when to check back (~45 min).

Pipeline: (1) Context Loading, (2) Data Extraction, (3) Party Identification, (4) Research, (5) AI Analysis with 18+ analyzers, (6) Instant Swarm™ redlining, (7) Email Generation, (8) Synthesis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNameNoOriginal filename of the document. If using filePath, this is extracted automatically.
filePathNoRECOMMENDED: Absolute path to the DOCX file on disk (e.g., "/Users/john/Documents/contract.docx"). The server will read and encode the file automatically.
industryNoIndustry context for analysis. Affects regulatory considerations and benchmarks.
dealValueNoEstimated deal value / annual contract value (ACV). Helps calibrate risk thresholds.
docxBase64NoAlternative: The contract document already encoded as base64 string (DOCX format). Use filePath instead if possible.
perspectiveNoDEPRECATED: Use representingParty instead
emailContextNoAdditional context for email generation
analysisDepthNoAnalysis depth: quick (~10 min), standard (~30 min), deep (~45 min). Default: standard
emailRecipientNoWho should the email be addressed to? counterparty=send to other side, client=internal summary, none=skip email
paperOwnershipNoWho drafted the contract? their-paper=counterparty drafted (default, full analysis), our-paper=we drafted (review their markup only)
enableAutoSwarmNoEnable parallel 17-section SAC analysis for comprehensive redlines. Default: true
additionalContextNoFree-form context about the deal: relationship history, priorities, concerns, red lines, etc.
dealValueCurrencyNoCurrency for deal value. Default: USD
representingPartyNoREQUIRED: Who are you representing? customer=buyer, vendor=seller, neutral=balanced review
aggressivenessLevelNoIMPORTANT: Redline aggressiveness 1-10. 1=very conciliatory (accept most terms), 5=balanced (default), 10=very aggressive (push hard on everything)
enableEmailGeneratorNoGenerate a negotiation email summarizing redlines? Default: true
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds context beyond annotations by detailing the 8-stage pipeline and the estimated 45-minute turnaround. It does not contradict annotations, which indicate a non-destructive mutation. Behavioral traits like timing and multi-step processing are well disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear warning banner, bulleted questions, and a pipeline list. It is slightly verbose but each section serves a purpose. The front-loading of usage instructions is effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, required user inputs, pipeline steps, and timing. It lacks explicit return value details (no output schema), but the mention of 'importantNote' partially compensates. For a complex tool, it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema description coverage is 100%, the description adds significant value by explaining which parameters are required to ask the user (e.g., representingParty, aggressivenessLevel) and providing usage context for others (e.g., paperOwnership, email fields). This exceeds baseline expectations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool processes a contract through a full 8-stage pipeline, distinguishing it from sibling tools that focus on specific subtasks. The verb 'process' and resource 'contract' are specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit instructions on what information to gather from the user before calling, including required and recommended questions. However, it does not explicitly state when to use this tool versus alternatives like quick_scan or instant_swarm.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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